15012 results for "cancer studies using rna-seq"

in 14.96 milliseconds.

• Inter and intra - tumor heterogeneity in Colorectal Cancer

  The dataset consists of two main sample groups. 1) The inter-tumour sample group contains a total of 97 samples from 27 patients. Each patient has a single normal and primary sample as well as one or more metastases. All samples were sequenced using IonTorrent PGM and a custom colorectal cancer (CRC) panel. 2) The intra-tumour sample group contains a total of 68 samples from a single tumour as well as a normal tissue sample. All 68 samples were sequenced using IonTorrent PGM and a custom CRC panel. Shallow whole genome sequencing was additionally applied to 10 of the samples using Illumina HiSeq 4000.

  Dataset EGAD00001003131

• Deep single-cell RNA sequencing data for 11138 T cells from tumour, adjacent normal tissue and peripheral blood of treatment-naive CRC patients. The DATA ACCESS AGREEMENT is provided at https://github.com/zhangyybio/single-T-cell-data-access. Applicants can request access to the data by directly downloading it or by sending an email to cancerpku@pku.edu.cn. The process that is used to approve an application includes verifying the institution, participants and research purposes of the application. In general this process will take about two weeks. In principal, any scientific research program complying with the laws and bioethic regulation policies of China will be approved.

  T cells are central players in cancer immunotherapy1, yet some of their fundamental properties such as development and migration within tumours remain elusive. The enormous T cell receptor (TCR) repertoire, required for recognising foreign and self-antigens2,3, could serve as lineage tags to track these T cells in tumours4. Here, we obtained transcriptomes of 11,138 single T cells from 12 colorectal cancer (CRC) patients and developed STARTRAC (Single T-cell Analysis by Rna-seq and Tcr TRACking) indices to quantitatively analyse dynamic relationships among 20 identified T cell subsets with distinct functions and clonalities. While both CD8+ effector and “exhausted” T cells exhibited high clonal expansion, they were independently connected with tumour-resident CD8+ effector memory cells, implicating a TCR-based fate decision. Of the CD4+ T cells, the majority of tumour-infiltrating Tregs showed clonal exclusivity, whereas certain Treg clones were developmentally linked to multiple TH clones. Notably, we identified two IFNG+ TH1-like clusters in tumours, the GZMK+ TEM and CXCL13+ TH1-like clusters, which were associated with distinct IFN-γ-regulating transcription factors, EOMES/RUNX3 and BHLHE40, respectively. Only CXCL13+BHLHE40+ TH1-like cells were preferentially enriched in tumours of microsatellite-instable (MSI) patients, which might explain their favourable response rates to immune-checkpoint blockade. Furthermore, we found IGFLR1 to be highly expressed in both CXCL13+BHLHE40+ TH1-like and CD8+ exhausted T cells and possessed co-stimulatory functions. Our integrated STARTRAC analyses provides a powerful avenue to comprehensively dissect the T cell properties in CRC, which could shed new insights into the dynamic relationships of T cells in other cancers

  Study EGAS00001002791

• Total RNA sequencing data from the Triple Negative Trial (TNT)

  BAM files from total RNA sequencing of samples from breast cancer patients in the TNT trial. Data includes 186 primary tumour samples and 13 matched recurrence samples.

  Dataset EGAD00001011141

• Sequencing_of_patient_samples_who_received_immune_checkpoint_inhibition___WES___NKI

  DNA and RNA isolated from FFPE blocks of patients who received immune checkpoint inhibition (ICI) are sequenced with the aim to identify therapeutically tractable vulnerabilities in tumors to prevent ICI resistance.

  Study EGAS00001003154

• Integrated Analysis of Multimodal Single-Cell Data

  The simultaneous measurement of multiple modalities, known as multimodal analysis, represents an exciting frontier for single cell genomics and necessitates new computational methods that can define cellular states based on multiple data types. Here, we introduce 'weighted nearest neighbor' analysis, an unsupervised framework to learn the relative utility of each data type in each cell, enabling an integrative analysis of multiple modalities. We apply our procedure to a CITE-seq dataset of hundreds of thousands of human white blood cells alongside a panel of 228 antibodies to construct a multimodal reference atlas of the circulating immune system. We demonstrate that integrative analysis substantially improves our ability to resolve cell states and validate the presence of previously unreported lymphoid subpopulations. Moreover, we demonstrate how to leverage this reference to rapidly map new datasets, and to interpret immune responses to vaccination and COVID-19. Our approach represents a broadly applicable strategy to analyze single-cell multimodal datasets, including paired measurements of RNA and chromatin state, and to look beyond the transcriptome towards a unified and multimodal definition of cellular identity. All CITE-seq and ECCITE-seq raw matrices are available in GEO database under the accession number GEO: GSE164378.

  Study phs002315

• Cord blood progenitor CITE-seq dataset

  Sequencing results of single-cell transcriptome and antibody libraries from two biological experiments of cord blood progenitor cells. Four samples from different time points were processed using 10X Genomics Chromium Next GEM Single Cell 3’ Reagent Kits v3.1. Gene expression and antibody-derived libraries were sequenced separately.

  Dataset EGAD50000000405

• Transcriptomics sequencing 4 samples from the same KMT2A-rearranged Acute Lymphoblastic Leukemia patient

  Dataset contains four samples taken from a neonate with congenital KMT2A-rearranged Acute Lymphoblastic Leukemia patient (CHI-0391) with rare IKZF1 gene fusions. Sequencing was carried out using mRNA-seq sequencing on a Illumina NextSeq 500 machine

  Dataset EGAD00001009974

• A Single-cell Atlas of Progressive TKI Resistance in Chronic Myeloid Leukemia

  57 Bone marrow specimens for 5 healthy bone marrow and 24 CML samples profiled with 10X scRNA-seq 5' upon separation using MACS for CD34.

  Dataset EGAD00001007946

• Unraveling the transcriptomic profile of utero-tubal lavage fluid of ovarian cancer patients

  mRNA capture seq of uterotubal lavage samples

  Dataset EGAD00001007933

• HGSOC-celllines-SmartSeq3

  Smart-seq3 scRNA-seq of cells from primary (OV2295) and metastatic (OV2295R2) high-grade serous ovarian cancer cell-line

  Dataset EGAD00001009798

• Nivolumab and Ipilimumab and Radiation Therapy in Microsatellite Stable (MSS) and Microsatellite Instable (MSI) High Colorectal and Pancreatic Cancer

  This is a single-arm, non-randomized, phase 2 trial (NCT03104439) combining radiation, ipilimumab and nivolumab in patients with metastatic MSS Colorectal Cancer (CRC; n=40) and Pancreatic Ductal Adenocarcinoma Cancer (PDAC; n=25). Patients were previously treated population, and the primary endpoint was disease control rate. Pre- and post-treatment samples were subjected to RNA sequencing and whole exome sequencing. The primary data is shared via GEO and dbGaP at National Center for Biotechnology Information (NCBI), National Institutes of Health (NIH).

  Study phs002545

• Arcagen - Extra-pulmonary neuroendocrine tumour or cancer grade 3 (NET / NEC G3) domain

  Arcagen is an EORTC/SPECTA pan-European project that aims to recruit 1000 rare cancer patients from different tumour domains of EURACAN. This study collected samples from advanced or metastatic rare cancer from patients older than 12, and analysed them using Foundation Medicine next-generation sequencing (NGS) panels (FoundationOne CDx for FFPE samples or FoundationOne Liquid CDx for blood samples). Here were are submitting the dataset that contains NGS files from patients with extra-pulmonary neuroendocrine tumour or cancer grade 3 (NET / NEC G3) (n=85).

  Study EGAS50000000644

• FinHer_Breast_Cancer_Study

  The purpose of this study is to sequence 500 known cancer genes in 960 newly diagnosed high risk breast cancer patients treated with current standard of care therapies and trastuzumab, for somatic alteration and copy number changes. We will be using next gen sequencing technology to determine the prognostic relevance of these somatic genetic alterations and of teh low frequency events to determine if they are associated with trastuzumab benefit or HER2 positive breast cancer, i.e. treatment interaction. The samples will be analysed adn correlated with clinical variables including outcome.

  Study EGAS00001000648

• WES in Angolan and Cape Verdean triple-negative breast cancer samples

  WES (using the SureSelect Human All Exon V5 + UTRs target enrichment kit) in 23 Angolan and 7 Cape Verdean triple-negative breast cancer samples

  Dataset EGAD50000001482

• Dataset for hepatopancreaticobiliary_malignancy-WHOLE_GENOME

  Rare cancer sequencing data of 83 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008884